pdrtpy 2.0b3

PhotoDissociation Region Toolbox (PDRT), astrophysics analysis tools

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pdrtpy is the new and improved version of the classic PhotoDissociation Region Toolbox, rewritten in Python with new capabilities and giving more flexibility to end users.

The new PDR Toolbox will cover many more spectral lines and metallicities and allows map-based analysis so users can quickly compute spatial images of density and radiation field from map data. We provide example Jupyter notebooks for data analysis. It also can support other PDR model codes enabling comparison of derived properties between codes.

The underlying model code has improved physics and chemistry. Critical updates include those discussed in Neufeld & Wolfire 2016, plus photo rates from Heays et al. 2017, oxygen chemistry rates from Kovalenko et al. 2018 and Tran et al. 2018, and carbon chemistry rates from Dagdigian 2019. We have also implemented new collisional excitation rates for [O I] from Lique et al. 2018 (and Lique private communication) and have included ¹³C chemistry along with the emitted line intensities for [¹³C II] and ¹³CO

Getting Started

Installation

pdrtpy can be installed with

pip install pdrtpy

or

git clone https://github.com/mpound/pdrtpy
sudo apt-get install python3-venv
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Requirements

Python 3 and recent versions of astropy, numpy, scipy, matplotlib. And jupyter if you want to run the example notebooks.

What is a PDR?

Photodissociation regions (PDRs) include all of the neutral gas in the ISM where far-ultraviolet (FUV) photons dominate the chemistry and/or heating. In regions of massive star formation, PDRS are created at the boundaries between the HII regions and neutral molecular cloud, as photons with energies 6 eV < E < 13.6 eV photodissociate molecules and photoionize other elements. The gas is heated from photo-electrons and cools mostly through far-infrared fine structure lines like [O I] and [C II].

For a full review of PDR physics and chemistry, see Hollenbach & Tielens 1997.